Robust scheduling optimization for flexible manufacturing systems with replenishment under uncertain machine failure disruptions

• Published in: Control engineering practice 2019-11, Vol.92, p.104094, Article 104094
• Main Authors: Wang, Zhiguo, Pang, Chee Khiang, Ng, Tsan Sheng
• Format: Article
• Language: English
• Subjects: Distributionally robust optimization; Flexible manufacturing systems (FMSs); Machine failure disruption; Mixed-integer linear program (MILP)
• ISSN: 0967-0661; 1873-6939
• DOI: 10.1016/j.conengprac.2019.07.012

This paper studies the scheduling problem for the flexible manufacturing systems (FMSs) under uncertain machine failure disruptions, where machine allocations and job schedules need to be determined to achieve a set of production due-date requirements as well as possible. A robust scheduling optimization model is proposed based on the concept of threshold scenario, bounded by which the due-dates are guaranteed to be achieved. It is shown that the associated stochastic scheduling problem can be equivalently solved by computing the solution of a mixed-integer linear program (MILP). Computational results show that our proposed model performs well in achieving the planned due-dates under uncertainty when compared to various standard approaches. The practical applicability of our approach is verified using a real stamping industry application, in which the stamping parts are various types of voice coil motor yokes used in commercial hard disk drive actuators. Apart from FMSs, the proposed approach can also be applied to various other industries including project scheduling, airline scheduling, transportation scheduling. •Robust optimization model based on the concept of threshold scenario is developed.•Uncertain disruptions of machine failure and replenishment is studied.•The optimal schedule can be computed by solving a mixed-integer linear program.•Higher success rate in meeting the due-dates is achieved under uncertainty.